In order to evaluate our framework in different domains and languages we used three publicly available offensive language detection datasets. As an off-domain English dataset, we choose the Offensive Language Identification Dataset (OLID) [1]}, used in OffensEval 2019 (SemEval-2019 Task 6) [2]}, containing over 14,000 posts from Twitter. To evaluate our framework in different languages, we selected a Danish [3]} and a Greek [4]} dataset. These two datasets have been provided by the organizers of OffensEval 2020 (SemEval-2020 Task 12) [5]} and were annotated using OLID's annotation guidelines. The Danish dataset contains over 3,000 posts from Facebook and Reddit while the Greek dataset contains over 10,000 Twitter posts, allowing us to evaluate our dataset in an off-domain, multilingual setting. As these three datasets have been annotated at the instance level, we followed an evaluation process explained in Section .
